This repository contains Machine Learning Lab cycle programs.

Implementations of essential machine learning algorithms from scratch

Plain python implementations of basic machine learning algorithms

Machine learning algorithms are computational models that allow computers to understand patterns and forecast or make judgments based on data without the need for explicit programming. These algorithms form the foundation of modern artificial intelligence and are used in a wide range of applications, including image and speech recognition.

Pathway is a high-throughput, low-latency data processing framework that handles live data & streaming for you. Made with ❤️ for Python & ML/AI developers.

Predict future stock prices with this Streamlit web app. Choose a company, set the forecast period, and visualize historical data and forecasted trends. Powered by machine learning with the Prophet library. Try it now!

Template for machine learning projects, featuring a diverse collection of ML models, AutoML solutions, and simple EDA tools for streamlined project development. Users only need to specify target features and add their data path in the Config to kickstart a wide array of machine learning tasks

oneAPI Data Analytics Library (oneDAL)

Trabalho de Big Data | Estácio

Focusing on Sentiment Analysis .

Machine learning algorithms for many-body quantum systems

The aim of this project was to research and develop a machine learning model for predicting the likelihood of a late delivery

Practice files of various ML algorithms that I learn throughout my journey are posted here.

This is a collection of all the machine learning techniques required in any machine learning project. It contains detailed descriptions, videos, book recommendations, and additional material to properly grasp all the concepts. It also contains implementations in various frameworks.

Analyse von Datensätzen mit verschiedenen ML-Algorithmen

Here I share my solutions to data analysis and coding interviews

This repository contains an implementation of decision tree and random forest algorithms from scratch in Python. Decision trees and random forests are popular machine learning algorithms used for classification and regression tasks. The goal of this project is to provide a clear and understandable implementation of these algorithms

HalfStack - ECHO - A Progressive Web App (PWA) that recommends songs and shows visualise statistics based on analysis of songs you already like on Spotify. Using a sentiment analysis AI to generate data on abstract song characteristics, like theme ,mood, bpm, key and time signature.